This course in artificial intelligence will provide a deep dive into advanced computer vision techniques for reasoning about visual data, and their real-world use in biomedicine. We will cover current cutting-edge models including different families of vision foundation models from representation learners to diffusion and generative models, and both vision-only and vision-language models. We will also cover considerations for real-world use, including model size and computation, training and inference settings, and training data, focusing on applications in biomedicine. Students will be actively engaged in studying and analyzing recent advancements through written analyses, class discussions, and a final project. This course is considered an advanced course and students should be comfortable with deep learning and computer vision at the level of CS 231N or BIODS220.
3 units · Medical Option (Med-Ltr-CR/NC)
This course in artificial intelligence will provide a deep dive into advanced computer vision techniques for reasoning about visual data, and their real-world use in biomedicine. We will cover current cutting-edge models including different families of vision foundation models from representation learners to diffusion and generative models, and both vision-only and vision-language models. We will also cover considerations for real-world use, including model size and computation, training and inference settings, and training data, focusing on applications in biomedicine. Students will be actively engaged in studying and analyzing recent advancements through written analyses, class discussions, and a final project. This course is considered an advanced course and students should be comfortable with deep learning and computer vision at the level of CS231N or BIODS220.
Offered in Autumn 2026 at Stanford University.